Most current augmented reality (AR) displays present content at a fixed focal demand. At the same time, real-world stimuli can occur at a variety of focal distances. To integrate information, users need to switch eye focus between virtual and real-world information continuously. Previously, Gabbard, Mehra, and Swan (2018) examined these issues, using a text-based visual search task on a monocular AR display. This thesis replicated and extended the previous experiment by including a new experimental variable stereopsis (stereo, mono) and fully crossing the variables of context switching and focal distance switching, using AR haploscope. The results from the monocular condition indicate successful replication, which is consistent with the hypothesis that the findings are a general property of AR. The outcome of the stereo condition supports the same adverse effects of context switching and focal distance switching. Further, participants have better performance and less eye fatigue in the stereo condition compared to the monocular condition.

In augmented reality, information is often distributed between real and virtual contexts, and often appears at different distances from the viewer. This raises the issues of (1) context switching, when attention is switched between real and virtual contexts, (2) focal distance switching, when the eye accommodates to see information in sharp focus at a new distance, and (3) transient focal blur, when information is seen out of focus, during the time interval of focal distance switching. This dissertation research has quantified the impact of context switching, focal distance switching, and transient focal blur on human performance and eye fatigue in both monocular and binocular viewing conditions. Further, this research has developed a novel font that when seen out-of-focus looks sharper than standard fonts. This SharpView font promises to mitigate the effect of transient focal blur. Developing this font has required (1) mathematically modeling out-of-focus blur with Zernike polynomials, which model focal deficiencies of human vision, (2) developing a focus correction algorithm based on total variation optimization, which corrects out-of-focus blur, and (3) developing a novel algorithm for measuring font sharpness. Finally, this research has validated these fonts through simulation and optical camera-based measurement. This validation has shown that, when seen out of focus, SharpView fonts are as much as 40 to 50% sharper than standard fonts. This promises to improve font legibility in many applications of augmented reality.

El presente trabajo se basa en el diseño de un sistema de seguridad física, aplicando tecnología de reconocimiento facial, para el control de acceso en una empresa del sector minero, este sistema permite tener un control robusto y confiable de los usuarios que ingresan y transitan por el campamento minero, este sistema se adapta a la nueva realidad que estamos viviendo, donde el distanciamiento social, el contacto físico personal y la medición de la temperatura, es un requisito indispensable. El diseño propuesto toma como referencia las mejores prácticas de las normas IEC 80601-2-59:2017 e ISO/TR 13154:2017, así como las recomendaciones del NISTIR 8238 que nos habla sobre la prueba continua de proveedores de reconocimiento facial. La problemática actual, es con referencia a la desactualización tecnología que tienen casi el 90% de los sistemas de seguridad de las empresas del sector minero, ya que, tras la llegada de la pandemia, estos sistemas se vieron evidenciados del pobre avance tecnológico con el que contaban. El diseño propuesto integra el uso de algoritmos con inteligencia artificial que permiten automatizar el proceso de identificación de los usuarios a través de su rostro, utilizando el flujo de video de las cámaras, analizamos la cobertura de las áreas a cubrir a través de los cálculos ópticos y distancia focal de las cámaras, proponemos también un mecanismo de gestión y tratamiento de las alertas que se generen de las analíticas aplicadas. Finalmente realizamos una comprobación y evidenciamos los resultados del diseño para cada objetivo específico planteado. / This work is based on the design of a physical security system, applying facial recognition technology, for access control in a company in the mining sector, this system allows to have a robust and reliable control of users entering and passing through the mining camp, this system adapts to the new reality we are living, where social distancing, personal physical contact, and temperature measurement, are indispensable requirements. The proposed design takes as a reference the best practices of the IEC 80601-2-59:2017 and ISO/TR 13154:2017 standards, as well as the recommendations of the NISTIR 8238 that tells us about the continuous testing of facial recognition providers. The current problem is related to the technological outdatedness of almost 90% of the security systems of the companies in the mining sector, since, after the arrival of the pandemic, these systems were evidenced by the poor technological progress they had. The proposed design integrates the use of algorithms with artificial intelligence that allow us to automate the process of identifying users through their face, using the video flow of the cameras, we analyse the coverage of the areas to be covered through optical calculations and focal length of the cameras, we also propose a mechanism for the management and treatment of alerts generated from applied analytics. Finally, we verify and show the results of the design for each specific objective set previously. / Tesis